Biophysical Parameters Research Articles

Quantifying turgor pressure in budding and fission yeasts based upon osmotic properties

Walled cells, such as plants, fungi, and bacteria cells, possess a high internal hydrostatic pressure, termed turgor pressure, that drives volume growth and contributes to cell shape determination. Rigorous measurement of turgor pressure, however, remains challenging, and reliable quantitative measurements, even in budding yeast are still lacking. Here, we present a simple and robust experimental approach to access turgor pressure in yeasts based upon the determination of isotonic concentration using protoplasts as osmometers. We propose three methods to identify the isotonic condition – three-dimensional cell volume, cytoplasmic fluorophore intensity, and mobility of a cytGEMs nano-rheology probe – that all yield consistent values. Our results provide turgor pressure estimates of 1.0 ± 0.1 MPa for Schizosaccharomyces pombe, 0.49 ± 0.01 MPa for Schizosaccharomyces japonicus, 0.5 ± 0.1 MPa for Saccharomyces cerevisiae W303a and 0.31 ± 0.03 MPa for Saccharomyces cerevisiae BY4741. Large differences in turgor pressure and nano-rheology measurements between the Saccharomyces cerevisiae strains demonstrate how fundamental biophysical parameters can vary even among wild-type strains of the same species. These side-by-side measurements of turgor pressure in multiple yeast species provide critical values for quantitative studies on cellular mechanics and comparative evolution.

Development of Essential Oil-Loaded Polymeric Nanocapsules as Skin Delivery Systems: Biophysical Parameters and Dermatokinetics Ex Vivo Evaluation.

Essential oils (EOs) are natural antioxidant alternatives that reduce skin damage. However, EOs are highly volatile; therefore, their nanoencapsulation represents a feasible alternative to increase their stability and favor their residence time on the skin to guarantee their effect. In this study, EOs of Rosmarinus officinalis and Lavandula dentata were nanoencapsulated and evaluated as skin delivery systems with potential antioxidant activity. The EOs were characterized and incorporated into polymeric nanocapsules (NC-EOs) using nanoprecipitation. The antioxidant activity was evaluated using the ferric thiocyanate method. The ex vivo effects on pig skin were evaluated based on biophysical parameters using bioengineering techniques. An ex vivo dermatokinetic evaluation on pig skin was performed using modified Franz cells and the tape-stripping technique. The results showed that the EOs had good antioxidant activity (>65%), which was maintained after nanoencapsulation and purification. The nanoencapsulation of the EOs favored its deposition in the stratum corneum compared to free EOs; the highest deposition rate was obtained for 1,8-cineole, a major component of L. dentata, at 1 h contact time, compared to R. officinalis with a major deposition of the camphor component. In conclusion, NC-EOs can be used as an alternative antioxidant for skin care.

Form factor determination of biological molecules with X-ray free electron laser small-angle scattering (XFEL-SAS)

Free-electron lasers (FEL) are revolutionizing X-ray-based structural biology methods. While protein crystallography is already routinely performed at FELs, Small Angle X-ray Scattering (SAXS) studies of biological macromolecules are not as prevalent. SAXS allows the study of the shape and overall structure of proteins and nucleic acids in solution, in a quasi-native environment. In solution, chemical and biophysical parameters that have an influence on the structure and dynamics of molecules can be varied and their effect on conformational changes can be monitored in time-resolved XFEL and SAXS experiments. We report here the collection of scattering form factors of proteins in solution using FEL X-rays. The form factors correspond to the scattering signal of the protein ensemble alone; the scattering contributions from the solvent and the instrument are separately measured and accurately subtracted. The experiment was done using a liquid jet for sample delivery. These results pave the way for time-resolved studies and measurements from dilute samples, capitalizing on the intense and short FEL X-ray pulses.

Evaluation of Coffee Plants Transplanted to an Area with Surface and Deep Liming Based on Multispectral Indices Acquired Using Unmanned Aerial Vehicles

The use of new technologies to monitor and evaluate the management of coffee crops allowed for a significant increase in productivity. Precision coffee farming has leveraged the development of this commodity by using remote sensing and Unmanned Aerial Vehicles (UAVs). However, the success of coffee farming in the country also resulted from management practices, including liming management in the soils. This study aimed to evaluate the response of coffee seedlings transplanted to areas subjected to deep liming in comparison to conventional (surface) liming, using vegetation indices (VIs) generated by multispectral images acquired using UAVs. The study area was overflown bimonthly by UAVs to measure the plant height, crown diameter, and chlorophyll content in the field. The VIs were generated and compared with the data measured in the field using linear time graphs and a correlation analysis. Linear regression was performed to predict the biophysical parameters as a function of the VIs. A significant difference was found only in the chlorophyll content. Most indices were correlated with the biophysical parameters, particularly the green chlorophyll index (GCI) and the canopy area calculated via vectorization. Therefore, UAVs proved to be effective coffee monitoring tools and can be recommended for coffee producers.

Scanning single molecule localization microscopy (scanSMLM) for super-resolution volume imaging

Over the last decade, single-molecule localization microscopy (SMLM) has developed into a set of powerful techniques that have improved spatial resolution over diffraction-limited microscopy and demonstrated the ability to resolve biological features down to a few tens of nanometers. We introduce a single molecule-based scanning SMLM (scanSMLM) system that enables rapid volume imaging. Along with epi-illumination, the system employs a scanning-based 4f detection for volume imaging. The 4f system comprises a combination of an electrically-tunable lens and high NA detection objective lens. By rapidly changing the aperture (or equivalently the focus) of an electrically-tunable lens (ETL) in a 4f detection system, the selectivity of the axial object plane is achieved, for which the image forms in the image/detector plane. So, in principle, one can scan the object volume by just altering the aperture of ETL. Two schemes were adopted to carry out volume imaging: cyclic scan and conventional scan. The cyclic scheme scans the volume in each scan cycle, whereas plane-wise scanning is performed in the conventional scheme. Hence, the cyclic scan ensures uniform dwell time on each frame during data collection, thereby evenly distributing photobleaching throughout the cell volume. With a minimal change in the system hardware (requiring the addition of an ETL lens and related electronics for step-voltage generation) in the existing SMLM system, volume scanning (along the z-axis) can be achieved. To calibrate and derive critical system parameters, we imaged fluorescent beads embedded in a gel-matrix 3D block as a test sample. Subsequently, scanSMLM is employed to visualize the architecture of actin-filaments and the distribution of Meos-Tom20 molecules on the mitochondrial membrane. The technique is further exploited to understand the clustering of Hemagglutinin (HA) protein single molecules in a transfected cell for studying Influenza-A disease progression. The system, for the first time, enabled 3D visualization of HA distribution that revealed HA cluster formation spanning the entire cell volume, post 24 hrs of transfection. Critical biophysical parameters related to HA clusters (density, the number of HA molecules per cluster, axial span, fraction of clustered molecules, and others) are also determined, giving an unprecedented insight into Influenza-A disease progression at the single-molecule level.

Challenges in Imaging Analyses of Biomolecular Condensates in Cells Infected with Influenza A Virus.

Biomolecular condensates are crucial compartments within cells, relying on their material properties for function. They form and persist through weak, transient interactions, often undetectable by classical biochemical approaches. Hence, microscopy-based techniques have been the most reliable methods to detail the molecular mechanisms controlling their formation, material properties, and alterations, including dissolution or phase transitions due to cellular manipulation and disease, and to search for novel therapeutic strategies targeting biomolecular condensates. However, technical challenges in microscopy-based analysis persist. This paper discusses imaging, data acquisition, and analytical methodologies' advantages, challenges, and limitations in determining biophysical parameters explaining biomolecular condensate formation, dissolution, and phase transitions. In addition, we mention how machine learning is increasingly important for efficient image analysis, teaching programs what a condensate should resemble, aiding in the correlation and interpretation of information from diverse data sources. Influenza A virus forms liquid viral inclusions in the infected cell cytosol that serve as model biomolecular condensates for this study. Our previous work showcased the possibility of hardening these liquid inclusions, potentially leading to novel antiviral strategies. This was established using a framework involving live cell imaging to measure dynamics, internal rearrangement capacity, coalescence, and relaxation time. Additionally, we integrated thermodynamic characteristics by analysing fixed images through Z-projections. The aforementioned paper laid the foundation for this subsequent technical paper, which explores how different modalities in data acquisition and processing impact the robustness of results to detect bona fide phase transitions by measuring thermodynamic traits in fixed cells. Using solely this approach would greatly simplify screening pipelines. For this, we tested how single focal plane images, Z-projections, or volumetric analyses of images stained with antibodies or live tagged proteins altered the quantification of thermodynamic measurements. Customizing methodologies for different biomolecular condensates through advanced bioimaging significantly contributes to biological research and potential therapeutic advancements.

Right superior pulmonary vein parameter determined by three-dimensional transesophageal echocardiography is an independent predictor of the outcome after cryoballoon isolation of the pulmonary veins.

A direct comparison of three-dimensional transesophageal echocardiography (3DTEE) and cardiac computed tomography imaging has demonstrated good inter-technique agreement for the following pulmonary vein (PV) parameters: the ostium area of the right superior PV (RSPV) and its major (a) and minor axis (b) diameters, the left lateral ridge and the minor axis (b) diameter of the left superior PV. Herein, under investigation, was the predictive value of these parameters for arrhythmia recurrence (AR) after PV isolation with the 28 mm second generation cryoballoon (CBG2). One hundred eleven patients (67 men, mean age 58.06 ± 10.58 years) undergoing 3DTEE before PV isolation with the CBG2 for paroxysmal atrial fibrillation were followed. "Point by point" redo intervention was offered in case of AR and reconnected PVs were defined. During a mean follow-up of 617 ± 258.86 days, 65 (58.9%) patients remained free of AR. Longer RSPV b was found to be the only significant predictor for AR (hazard ratio [HR] 1.059; 95% confidence interval [CI] 1.000-1.121; p = 0.048). RSPV b ≥ 28 mm resulted in a threefold (HR 3.010; 95% CI 1.270-7.134, p = 0.012) increase in the risk of AR. The association of RSPV b with AR was independent of the biophysical parameters of cryoapplications. In 25 "redo" patients, reconnections were found 1.75 times more likely in the RSPV than in the other 3 PVs altogether. Right superior PV b measured with 3DTEE might be a significant predictor of AR after PV isolation with the CBG2. In case of RSPV b exceeding 28 mm, alternative PV isolation techniques or use of a larger balloon might be considered.

Analysis of dim-light responses in rod and cone photoreceptors with altered calcium kinetics

Rod and cone photoreceptors in the retina of vertebrates are the primary sensory neurons underlying vision. They convert light into an electrical current using a signal transduction pathway that depends on Ca^{2+} feedback. It is known that manipulating the Ca^{2+} kinetics affects the response shape and the photoreceptor sensitivity, but a precise quantification of these effects remains unclear. We have approached this task in mouse retina by combining numerical simulations with mathematical analysis. We consider a parsimonious phototransduction model that incorporates negative Ca^{2+} feedback onto the synthesis of cyclic GMP, and fast buffering reactions to alter the Ca^{2+} kinetics. We derive analytic results for the photoreceptor functioning in sufficiently dim light conditions depending on the photoreceptor type. We exploit these results to obtain conceptual and quantitative insight into how response waveform and amplitude depend on the underlying biophysical processes and the Ca^{2+} feedback. With a low amount of buffering, the Ca^{2+} concentration changes in proportion to the current, and responses to flashes of light are monophasic. With more buffering, the change in the Ca^{2+} concentration becomes delayed with respect to the current, which gives rise to a damped oscillation and a biphasic waveform. This shows that biphasic responses are not necessarily a manifestation of slow buffering reactions. We obtain analytic approximations for the peak flash amplitude as a function of the light intensity, which shows how the photoreceptor sensitivity depends on the biophysical parameters. Finally, we study how changing the extracellular Ca^{2+} concentration affects the response.

Assessing the Recent Trends of Land Degradation and Desertification in Romania Using Remote Sensing Indicators

Land degradation (LD) and desertification (DS) are a sensitive global issue including southern and south-eastern Europe, which is severely affected by climate change. In this study, a state-of-the-art approach for assessing the intensity of LD and DS processes using remote-sensing-derived indicators within a GIS environment was proposed. The analysis was carried out using the Principal Component Analysis based on integrating the significant trends of relevant biophysical parameters in Romania. The methodology was tested and validated at the national level in Romania. In total, 7.76% of the area was identified as LD and 60.8% of the total area tended to improve, and 31.44% was stable. Most of the regions with LD overlapped with the dryland areas, while improvement areas were identified outside of the drylands. In forested areas from high altitudes, a tendency to improve the condition of vegetation was observed, and most of the surfaces being protected were natural areas that have benefited from proper management. All these results can be used to adapt management practices to avoid, reduce, or restore the LD. The proposed model was based on globally available remote sensing datasets, with a high frequency of data acquisition and collection history that allows for the statistical analyses of changes on a global scale.

Staphylococcus aureus Modulates Carotenoid and Phospholipid Content in Response to Oxygen-Restricted Growth Conditions, Triggering Changes in Membrane Biophysical Properties.

Staphylococcus aureus membranes contain carotenoids formed during the biosynthesis of staphyloxanthin. These carotenoids are considered virulence factors due to their activity as scavengers of reactive oxygen species and as inhibitors of antimicrobial peptides. Here, we show that the growth of S. aureus under oxygen-restricting conditions downregulates carotenoid biosynthesis and modifies phospholipid content in biofilms and planktonic cells analyzed using LC-MS. At oxygen-restrictive levels, the staphyloxanthin precursor 4,4-diapophytofluene accumulates, indicating that the dehydrogenation reaction catalyzed by 4,4'-diapophytoene desaturases (CrtN) is inhibited. An increase in lysyl-phosphatidylglycerol is observed under oxygen-restrictive conditions in planktonic cells, and high levels of cardiolipin are detected in biofilms compared to planktonic cells. Under oxygen-restriction conditions, the biophysical parameters of S. aureus membranes show an increase in lipid headgroup spacing, as measured with Laurdan GP, and decreased bilayer core order, as measured with DPH anisotropy. An increase in the liquid-crystalline to gel phase melting temperature, as measured with FTIR, is also observed. S. aureus membranes are therefore less condensed under oxygen-restriction conditions at 37 °C. However, the lack of carotenoids leads to a highly ordered gel phase at low temperatures, around 15 °C. Carotenoids are therefore likely to be low in S. aureus found in tissues with low oxygen levels, such as abscesses, leading to altered membrane biophysical properties.

Approaches to classification of microembolic signals in patients recovering from ischemic stroke

Introduction. Microembolus detection by transcranial Doppler (TCD) is the only non-invasive modality for visualization of cerebral embolism. Currently, there is no unified classification of recorded microembolic signals (MES) that could be used in clinical practice.
 The aim of the study is to investigate biophysical MES parameters in patients with ischemic stroke, as well as to assess approaches to microemboli differentiation by structure and origin to improve the diagnostic accuracy of the method and to reduce the risk of recurrent ischemic events.
 Materials and methods. The inclusion criterion was TCD-detected signs of MES. We analyzed the data of 28 patients with ischemic stroke (9 women and 19 men; mean age was 58 years 13). We recorded power, duration, and frequency for each MES, and calculated an energy index.
 Results. A total of 938 MES were reported. In patients with cardioembolic stroke and all other pathogenetic stroke subtypes, biophysical parameter limits were as follows: 14.65 dB for the average power, 9.45 ms for the average duration, and 0.16 J for the average energy index. For patients with atrial fibrillation, characteristic MES power was found to be 13 dB. The MES frequency limit was determined to be 650 Hz for microemboli differentiation by acoustic density.
 Conclusion. The data obtained can be used to further search for optimal limit ranges for biophysical parameters of various MES in order to establish a single MES classification, which will increase the diagnostic value of microembolus detection by TCD in stroke treatment practice.

LAI estimation based on physical model combining airborne LiDAR waveform and Sentinel-2 imagery.

Leaf area index (LAI) is an important biophysical parameter of vegetation and serves as a significant indicator for assessing forest ecosystems. Multi-source remote sensing data enables large-scale and dynamic surface observations, providing effective data for quantifying various indices in forest and evaluating ecosystem changes. However, employing single-source remote sensing spectral or LiDAR waveform data poses limitations for LAI inversion, making the integration of multi-source remote sensing data a trend. Currently, the fusion of active and passive remote sensing data for LAI inversion primarily relies on empirical models, which are mainly constructed based on field measurements and do not provide a good explanation of the fusion mechanism. In this study, we aimed to estimate LAI based on physical model using both spectral imagery and LiDAR waveform, exploring whether data fusion improved the accuracy of LAI inversion. Specifically, based on the physical model geometric-optical and radiative transfer (GORT), a fusion strategy was designed for LAI inversion. To ensure inversion accuracy, we enhanced the data processing by introducing a constraint-based EM waveform decomposition method. Considering the spatial heterogeneity of canopy/ground reflectivity ratio in regional forests, calculation strategy was proposed to improve this parameter in inversion model. The results showed that the constraint-based EM waveform decomposition method improved the decomposition accuracy with an average 12% reduction in RMSE, yielding more accurate waveform energy parameters. The proposed calculation strategy for the canopy/ground reflectivity ratio, considering dynamic variation of parameter, effectively enhanced previous research that relied on a fixed value, thereby improving the inversion accuracy that increasing on the correlation by 5% to 10% and on R2 by 62.5% to 132.1%. Based on the inversion strategy we proposed, data fusion could effectively be used for LAI inversion. The inversion accuracy achieved using both spectral and LiDAR data (correlation=0.81, R2=0.65, RMSE=1.01) surpassed that of using spectral data or LiDAR alone. This study provides a new inversion strategy for large-scale and high-precision LAI inversion, supporting the field of LAI research.

The biophysical effects of potential changes in irrigated crops on diurnal land surface temperature in Northeast China

Irrigated crops have experienced a significant global expansion. The biophysical response of climate change to irrigated crop expansion in different regions, particularly in terms of monitoring the influence mechanism of nighttime land surface temperature (LST) change, however, remains insufficiently explored. Taking the three northeastern provinces of China as our study area, we apply window analysis, partial correlation analysis, and geographical detector to quantitatively characterize the spatial and temporal distribution pattern of daytime and nighttime LST (diurnal LST) and biophysical parameters, and the main driving mechanism of diurnal LST change. The results showed that irrigated crop expansion led to asymmetric changes in daytime (−2.11 ± 0.2°C, 97.4%) and nighttime (0.64 ± 0.2°C, 79.9%) LST. ΔLSTDT had a negative correlation with ΔLE (63%), but a positive correlation with ΔSSR and ΔH (91% and 77%). This revealed that the cooling effect caused by the superposition of the output latent heat flux and the absorbed solar shortwave radiation was greater than its heating effect. ΔLSTNT and ΔLE had a positive connection across 69% of the region. ΔLSTNT demonstrated a negative correlation with ΔSSR and ΔH in 82% and 75% of the regions, respectively. At this time, the superposition of latent heat flux and heating potential term produces a greater heating effect. The explanatory power of the single factor (the mean of q<0.50) of biophysical parameters for diurnal LST variation was significantly smaller than that of the interaction factor (the mean of q>0.50, p<0.01). This study shows more detailed dynamic information of diurnal LST and biophysical parameters from 8day scale. The findings highlighted the critical role of asymmetric changes in the diurnal surface thermal environment caused by irrigated crop expansion in the global climate from a land surface hydrothermal energy balance perspective.

Live-cell three-dimensional single-molecule tracking reveals modulation of enhancer dynamics by NuRD

To understand how the nucleosome remodeling and deacetylase (NuRD) complex regulates enhancers and enhancer–promoter interactions, we have developed an approach to segment and extract key biophysical parameters from live-cell three-dimensional single-molecule trajectories. Unexpectedly, this has revealed that NuRD binds to chromatin for minutes, decompacts chromatin structure and increases enhancer dynamics. We also uncovered a rare fast-diffusing state of enhancers and found that NuRD restricts the time spent in this state. Hi-C and Cut&Run experiments revealed that NuRD modulates enhancer–promoter interactions in active chromatin, allowing them to contact each other over longer distances. Furthermore, NuRD leads to a marked redistribution of CTCF and, in particular, cohesin. We propose that NuRD promotes a decondensed chromatin environment, where enhancers and promoters can contact each other over longer distances, and where the resetting of enhancer–promoter interactions brought about by the fast decondensed chromatin motions is reduced, leading to more stable, long-lived enhancer–promoter relationships.

Priority quality traits for gendered sweetpotato breeding in Mozambique

IntroductionSweetpotato breeders strive to develop varieties that address productivity challenges farmers face in sub-Saharan Africa (SSA). However, adoption of these varieties is low, partly attributed to limited attention to attributes desired by the end-users.MethodsThis study sought to identify the key traits preferred by eight women processors and 426 consumers (180 male, 246 female) in Manhiça, Marracuene and Maputo districts, Mozambique. Processing diagnostics and consumer studies evaluated two local varieties (‘Lilas’, ‘N’santimuni’) and two improved varieties (‘Alisha’, ‘Irene’). Data from processors were analyzed using content analysis and summary statistics. Consumer hedonic data were analyzed using clustering and regression models, while Penalty analysis and Multiple correspondence analysis were performed for the Just-about-right and Check-all-that-apply tests respectively.ResultsProcessors prioritized mealiness, sweet taste, not fibrous, good sweetpotato smell, ease of peeling, easy to cook and good appearance for the boiled root. ‘N’santimuni’ was the most preferred variety for processing. Consumers preferred ‘N’santimuni’ and ‘Lilas’ because of their high dry matter, pleasant sweetpotato smell, firmness in the hand, smoothness when eating and sweet taste. ‘Alisha’ and ‘Irene’ were the most penalized for low scores on sweetness, mealiness, and firmness. Women consumed sweetpotato more frequently than men and had better discernment of sweet taste, homogeneity and colour. Also, youth and more educated consumers disliked improved varieties more than adults and lower income consumers.DiscussionProcessors and consumers strongly indicated their preference and importance of quality attributes such as mealiness, sweet taste, firmness for boiled sweetpotato. However, such traits are rarely included in breeding designs. Breeding programs can thus be enhanced by studies of biophysical and chemical parameters of sweetpotato. This will enable quantification incorporation of these quality attributes.

A computational model to uncover the biophysical underpinnings of neural firing heterogeneity in dissociated hippocampal cultures.

Calcium (Ca2+ ) imaging reveals a variety of correlated firing in cultures of dissociated hippocampal neurons, pinpointing the non-synaptic paracrine release of glutamate as a possible mediator for such firing patterns, although the biophysical underpinnings remain unknown. An intriguing possibility is that extracellular glutamate could bind metabotropic receptors linked with inositol trisphosphate (IP3 ) mediated release of Ca2+ from the endoplasmic reticulum of individual neurons, thereby modulating neural activity in combination with sarco/endoplasmic reticulum Ca2+ transport ATPase (SERCA) and voltage-gated Ca2+ channels (VGCC). However, the possibility that such release may occur in different neuronal compartments and can be inherently stochastic poses challenges in the characterization of such interplay between various Ca2+ channels. Here we deploy biophysical modeling in association with Monte Carlo parameter sampling to characterize such interplay and successfully predict experimentally observed Ca2+ patterns. The results show that the neurotransmitter level at the plasma membrane is the extrinsic source of heterogeneity in somatic Ca2+ transients. Our analysis, in particular, identifies the origin of such heterogeneity to an intrinsic differentiation of hippocampal neurons in terms of multiple cellular properties pertaining to intracellular Ca2+ signaling, such as VGCC, IP3 receptor, and SERCA expression. In the future, the biophysical model and parameter estimation approach used in this study can be upgraded to predict the response of a system of interconnected neurons.

Spatio-temporal rainfall interception loss at the catchment scale from earth observation in a data-scarce area, Northern Ethiopia

Rainfall interception loss (EI) is an important spatio-temporal variable in hydrological studies. The EI is required as input of integrated hydrological models, which nowadays are increasingly applied in water resources management. However, the EI is typically not considered or arbitrarily simplified, which causes wrong model parameterization and typical overestimation of water resources. Such problem can be particularly consequential in water-limited environments, where EI represents a substantial percentage of rainfall. The EI is rarely quantified experimentally because field data acquisition for its direct estimation is cumbersome and costly, especially at large catchment/basin scales. Hence, Earth Observation Satellites (EOS) can be used as an alternative source of data acquisition to quantify EI, especially at large spatial scales. The main aim of this study was to estimate the daily variability of rainfall interception loss in the data-scarce Zamra catchment (1588 km2) in Ethiopia, applying the EOS solution of the revised Gash model (RGM). Next to EOS, this study utilized four automated weather station data. To test the RGM assumption permitting the use of rainfall as one storm per rainy day (instead of the event-based rainfall), high temporal resolution (15 min) automated weather-station data was used. The test confirmed the validity of that assumption in the Zamra catchment (ZC), so the daily bias-corrected by station data rainfall was used as input. The weather station data was also used to define the event-based ratio of the mean wet-canopy evaporation rate to the mean rainfall rate (Ec¯/R¯) ranging from ∼0.037 to 0.041 at the low-elevated stations to ∼0.063 at the high-elevated station. As the variability of the Ec¯/R¯ of the three low-elevated stations was pretty uniform, the mean 0.04 was assumed for areas below 2000 m a.s.l., but for the areas above, the Ec¯/R¯ was assigned as altitude-dependent applying geographical weighted regression method. Other biophysical parameters, the fractional canopy cover and the canopy storage capacity obtained from leaf area index, were derived from Sentinel 2. The final EI was highly spatially and temporally variable, ranging from zero at bare lands, to 30% of annual rainfall in forested areas and with ∼4% mean of annual rainfall for the whole ZC. While applying EOS solution of RGM, facilitated with limited amount of ground-based data, the presented study offers an efficient and realistic way of spatio-temporal quantification of EI, particularly suitable for large data-scarce areas such as the ZC.

Leaf Area Index Inversion of Spartina alterniflora Using UAV Hyperspectral Data Based on Multiple Optimized Machine Learning Algorithms

The leaf area index (LAI) is an essential biophysical parameter for describing the vegetation canopy structure and predicting its growth and productivity. Using unmanned aerial vehicle (UAV) hyperspectral imagery to accurately estimate the LAI is of great significance for Spartina alterniflora (S. alterniflora) growth status monitoring. In this study, UAV hyperspectral imagery and the LAI of S. alterniflora during the flourishing growth period were acquired. The hyperspectral data were preprocessed with Savitzky–Golay (SG) smoothing, and the first derivative (FD) and the second derivative (SD) spectral transformations of the data were then carried out. Then, using the band combination index (BCI) method, the characteristic bands related to the LAI were extracted from the hyperspectral image data obtained with the UAV, and spectral indices (SIs) were constructed through the characteristic bands. Finally, three machine learning (ML) regression methods—optimized support vector regression (OSVR), optimized random forest regression (ORFR), and optimized extreme gradient boosting regression (OXGBoostR)—were used to establish LAI estimation models. The results showed the following: (1) the three ML methods accurately predicted the LAI, and the optimal model was provided by the ORFR method, with an R2 of 0.85, an RMSE of 0.19, and an RPD of 4.33; (2) the combination of FD SIs improved the model accuracy, with the R2 value improving by 41.7%; (3) the band combinations screened using the BCI method were mainly concentrated in the red and near-infrared bands; (4) the higher LAI was distributed on the seaward side of the study area, while the lower LAI was located at the junction between the S. alterniflora and the tidal flat. This study serves as both theoretical and technological support for research on the LAI of S. alterniflora and as a solid foundation for the use of UAV remote sensing technologies in the supervisory control of S. alterniflora.

Analysis of structural effects of sickle cell disease on brain vasculature of mice using three-dimensional quantitative phase imaging.

Although the molecular origins of sickle cell disease (SCD) have been extensively studied, the effects of SCD on the vasculature-which can influence blood clotting mechanisms, pain crises, and strokes-are not well understood. Improving this understanding can yield insight into the mechanisms and wide-ranging effects of this devastating disease. We aim to demonstrate the ability of a label-free 3D quantitative phase imaging technology, called quantitative oblique back-illumination microscopy (qOBM), to provide insight into the effects of SCD on brain vasculature. Using qOBM, we quantitatively analyze the vasculature of freshly excised, but otherwise unaltered, whole mouse brains. We use Townes sickle transgenic mice, which closely recapitulate the pathophysiology of human SCD, and sickle cell trait mice as controls. Two developmental time points are studied: 6-week-old mice and 20-week-old mice. Quantitative structural and biophysical parameters of the vessels (including the refractive index (RI), which is linearly proportional to dry mass) are extracted from the high-resolution images and analyzed. qOBM reveals structural differences in the brain blood vessel thickness (thinner for SCD in particular brain regions) and the RI of the vessel wall (higher and containing a larger variation throughout the brain for SCD). These changes were only significant in 20-week-old mice. Further, vessel breakages are observed in SCD mice at both time points. The vessel wall RI distribution near these breaks, up to away from the breaking point, shows an erratic behavior characterized by wide RI variations. Vessel diameter, tortuosity, texture within the vessel, and structural fractal patterns are found to not be statistically different. As with vessel breaks, we also observe blood vessel blockages only in mice brains with SCD. qOBM provides insight into the biophysical and structural composition of brain blood vessels in mice with SCD. Data suggest that the RI may be an indirect indicator of vessel rigidity, vessel strength, and/or tensions, which change with SCD. Future ex vivo and in vivo studies with qOBM could improve our understanding of SCD.

Assessment of Maize Crop Evapotranspiration Using Eddy Covariance Flux Tower Weather Data

The study conducted at the Maize Research Centre, Agriculture Research Institute, Professor Jayashankar Telangana State Agricultural University (PJTSAU), Rajendranagar, Hyderabad, from November, 2022 to March, 2023 aimed to compute the crop evapotranspiration (ETc) of maize crop under two different irrigation treatments using the weather data generated from the Eddy Covariance (EC) flux tower. The two treatments comprise of scheduling irrigation at certain Depletion of Available Soil Moisture (DASM) viz., T1: 20% DASM and T2: 40% DASM. The maize crop was sown and cultivated as per the recommended practices. The bio-physical parameters like plant height and LAI were recorded at 15 days interval. These parameters were statistically analysed by two sample T-test with equal variance. The plant height increased from 35 to 198 cm in 20% DASM and 36 to 180 cm in 40% DASM during the crop growth period (30 to 100 DAS). Similarly, LAI increased from 0.72 to 3.9 and 0.77 to 3.2 in 20 and 40 % DASM treatments till 90 DAS, respectively and later on decreased till harvest. The findings emphasize a positive influence of optimum moisture availability in the root zone on plant growth parameters. The amount of irrigation given was measured to compute ETc using Soil Water Balance (SWB) method and the crop parameters like plant height, LAI, stomatal resistance values etc., were used for computing the Penman-Monteith equation using the weather parameters generated from the EC flux tower. Seasonal ETc estimated from the Soil Water Balance (SWB) method (340 & 280 mm) and FAO Penman-Monteith method (350 & 295 mm) in 20 and 40% DASM treatments showed a deviation of +10 and +15 mm, respectively. Furthermore, the study concludes that FAO Penman-Monteith method can accurately estimate ET by using EC flux tower measured weather data, with minor deviations from the SWB method.